Spatially Resolved Transcriptomics Deconvolutes Histological Prognostic Subgroups in Patients with Colorectal Cancer and Synchronous Liver Metastases

Author:

Wood Colin S,Pennel Kathryn AF,Leslie Holly,Legrini Assya,Cameron Andrew J,Melissourgou-Syka Lydia,Quinn Jean A,van Wyk Hester C,Hay Jennifer,Roseweir Antonia K,Nixon Colin,Roxburgh Campbell SD,McMillan Donald C,Biankin Andrew V,Sansom Owen J,Horgan Paul G,Edwards Joanne,Steele Colin W,Jamieson Nigel BORCID

Abstract

ABSTRACTBackgroundPatients demonstrating strong immune responses to primary colorectal cancer (CRC) have a survival benefit following surgery, while those with predominantly stromal microenvironments do poorly. Biomarkers to identify patients with colorectal cancer liver metastases (CRLM) who have good prognosis following surgery for oligometastatic disease remain elusive. The aim of this study was to determine the practical application of a simple histological assessment of immune cell infiltration and stromal content in predicting outcome following synchronous resection of primary CRC and CRLM, and to interrogate the underlying functional biology that drives disease progression.MethodsPatients undergoing synchronous resection of primary CRC and CRLM underwent detailed histological assessment, panel genomic and bulk transcriptomic assessment, immunohistochemistry (IHC) and GeoMx Spatial Transcriptomics (ST) analysis. Integration with genomic features, pathway enrichment analysis and immune deconvolution were performed.ResultsHigh-immune metastases were associated with improved cancer specific survival (HR, 0.36, P=0.01). Bulk transcriptomic analysis was confounded by stromal content but ST demonstrated that the invasive edge of the metastases of long-term survivors was characterized by adaptive immune cell populations enriched for Type II Interferon signalling (NES=-2.05 P.Adj<0.005) and MHC-Class II Antigen Presentation (NES=-2.09 P.Adj<0.005). In contrast, patients with poor prognosis demonstrated increased abundance of regulatory T-cells and neutrophils with enrichment of Notch (NES=2.2 P.Adj=0.022) and TGF-β (NES=2.2 P.Adj=0.02) signalling pathways at the metastatic tumor centre.ConclusionsHistological assessment stratifies outcome in patients undergoing synchronous resection of CRLM. ST analysis reveals significant intra-tumoral and inter-lesional heterogeneity with underlying transcriptomic programmes identified in driving each phenotype.TRANSLATIONAL RELEVANCEThe current study demonstrates that accurate histological assessment of immune cell infiltration and stromal content can define survival in patients following resection of oligometastatic liver disease when presenting synchronously with primary colorectal cancer. A spatial transcriptomic approach has demonstrated heterogeneity between patients, between matched lesions in the same patient and within individual lesions. Patients with high immune infiltrates at the invasive margin demonstrated lymphocytic infiltration and associated upregulated adaptive immune pathways in long term survivors. In specimens with low immune infiltrate at the tumor edge a significant reduction in survival was observed, this was determined by upregulated immunosuppressive pathways and a predominance of innate immune cells surrounding metastases. Spatial transcriptomics can be used to examine drivers of metastatic progression in CRC and identifies patients with reactive and suppressed immune microenvironments. Application across a larger cohort will build the cartography of CRLM, while in future, studies may assess application of this technology to pre and post treatment biopsy samples with the aim of predicting individual therapeutic responses. The current study has highlighted discrepancies between bulk and ST derived data whilst demonstrating accuracy of deconvoluted transcriptome to determine immune profiling. Now that ST strategies are becoming more achievable at scale, this has implications for the interpretation of the bulk transcriptomic signatures both of primary and metastatic CRC.

Publisher

Cold Spring Harbor Laboratory

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